Adolescent THC impacts on mPFC dopamine-mediated cognitive processes in male and female rats
Bibliographic record
Abstract
Rationale: -tetrahydrocannabinol (THC) influences development of circuits underlying these processes, especially in the prefrontal cortex, which matures during adolescence. Objective: We determined how 14 daily THC injections (5mg/kg) during adolescence persistently impacts medial prefrontal cortex (mPFC) dopamine-dependent cognition. Methods: In adult Long Evans rats treated as adolescents with THC (AdoTHC), we quantify performance on two mPFC dopamine-dependent reward-based tasks-strategy set shifting and probabilistic discounting. We also determined how acute dopamine augmentation with amphetamine (0, 0.25, 0.5 mg/kg), or specific chemogenetic stimulation of ventral tegmental area (VTA) dopamine neurons and their projections to mPFC impacts probabilistic discounting. Results: AdoTHC sex-dependently impacts acquisition of cue-guided instrumental reward seeking, but has minimal effects on set-shifting or probabilistic discounting in either sex. When we challenged dopamine circuits acutely with amphetamine during probabilistic discounting, we found reduced discounting of improbable reward options, with AdoTHC rats being more sensitive to these effects than controls. In contrast, neither acute chemogenetic stimulation of VTA dopamine neurons nor pathway-specific chemogenetic stimulation of their projection to mPFC impacted probabilistic discounting in control rats, although stimulation of this cortical dopamine projection slightly disrupted choices in AdoTHC rats. Conclusions: These studies confirm a marked specificity in the cognitive processes impacted by AdoTHC exposure. They also suggest that some persistent AdoTHC effects may alter amphetamine-induced cognitive changes in a manner independent of VTA dopamine neurons or their projections to mPFC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".